{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "介绍如何在tensorflow环境下，使用FGSM算法攻击基于Inception数据集预训练的alexnet模型。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Jupyter notebook中使用Anaconda中的环境需要单独配置，默认情况下使用的是系统默认的Python环境，以使用advbox环境为例。\n",
    "首先在默认系统环境下执行以下命令，安装ipykernel。\n",
    "\n",
    "    conda install ipykernel\n",
    "    conda install -n advbox ipykernel\n",
    "\n",
    "在advbox环境下激活，这样启动后就可以在界面上看到advbox了。\n",
    "\n",
    "    python -m ipykernel install --user --name advbox --display-name advbox \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import logging\n",
    "logging.basicConfig(level=logging.INFO,format=\"%(filename)s[line:%(lineno)d] %(levelname)s %(message)s\")\n",
    "logger=logging.getLogger(__name__)\n",
    "\n",
    "import numpy as np\n",
    "from PIL import Image\n",
    "#pip install Pillow\n",
    "from adversarialbox.adversary import Adversary\n",
    "#from adversarialbox.attacks.gradient_method import FGSM\n",
    "from adversarialbox.attacks.gradient_method import FGSMT\n",
    "from adversarialbox.models.tensorflow import TensorflowModel\n",
    "import tensorflow as tf\n",
    "from tensorflow.examples.tutorials.mnist import input_data\n",
    "from tools import show_images_diff"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#定义被攻击的图片\n",
    "imagename=\"tutorials/cropped_panda.jpg\"\n",
    "#从'http://download.tensorflow.org/models/image/imagenet/inception-2015-12-05.tgz'下载并解压到当前路径\n",
    "dirname=\"classify_image_graph_def.pb\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "tensorflow.py[line:63] INFO self._input_shape:(Dimension(None), Dimension(None), Dimension(3))\n",
      "tensorflow.py[line:65] INFO init grads[1008]...\n",
      "tensorflow.py[line:72] INFO Finish TensorflowPBModel init\n",
      "base.py[line:87] INFO adversary:\n",
      "         original_label: 169\n",
      "         target_label: 651\n",
      "         is_targeted_attack: True\n",
      "gradient_method.py[line:86] INFO epsilons=10,epsilons_max=10,steps=100,epsilon_steps=1\n",
      "tensorflow.py[line:127] INFO Start to get _grads[651]\n",
      "tensorflow.py[line:129] INFO Finish to get _grads[651]\n",
      "gradient_method.py[line:133] INFO step=1, epsilon = 10.00000, pre_label = 169, adv_label=169 logits=11.2586631775\n",
      "gradient_method.py[line:133] INFO step=2, epsilon = 10.00000, pre_label = 169, adv_label=169 logits=8.53412723541\n",
      "gradient_method.py[line:133] INFO step=3, epsilon = 10.00000, pre_label = 169, adv_label=226 logits=5.82358455658\n",
      "gradient_method.py[line:133] INFO step=4, epsilon = 10.00000, pre_label = 169, adv_label=986 logits=6.51778793335\n",
      "gradient_method.py[line:133] INFO step=5, epsilon = 10.00000, pre_label = 169, adv_label=651 logits=10.8713703156\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "attack success, adversarial_label=651\n",
      "fgsm attack done\n"
     ]
    }
   ],
   "source": [
    "#加载解码的图像 这里是个大坑 tf提供的imagenet预训练好的模型pb文件中 包含针对图像的预处理环节 即解码jpg文件 这部分没有梯度\n",
    "#需要直接处理解码后的数据\n",
    "image=np.array(Image.open(imagename).convert('RGB').resize((224,224))).astype(np.float32)\n",
    "#[100,100,3]->[1,100,100,3]\n",
    "\n",
    "orig=image.copy().astype(np.uint8) \n",
    "\n",
    "image=np.expand_dims(image, axis=0)\n",
    "\n",
    "  \n",
    "\n",
    "session=tf.Session()\n",
    "\n",
    "def create_graph(dirname):\n",
    "    with tf.gfile.FastGFile(dirname, 'rb') as f:\n",
    "        graph_def = session.graph_def\n",
    "        graph_def.ParseFromString(f.read())\n",
    "\n",
    "        _ = tf.import_graph_def(graph_def, name='')\n",
    "\n",
    "create_graph(dirname)\n",
    "\n",
    "# 初始化参数  非常重要\n",
    "session.run(tf.global_variables_initializer())\n",
    "\n",
    "tensorlist=[n.name for n in session.graph_def.node]\n",
    "\n",
    "#输出全部tensor\n",
    "#logger.info(tensorlist)\n",
    "\n",
    "\n",
    "#获取logits\n",
    "logits=session.graph.get_tensor_by_name('softmax/logits:0')\n",
    "\n",
    "x = session.graph.get_tensor_by_name('ExpandDims:0')\n",
    "\n",
    "# advbox demo\n",
    "# 因为原始数据没有归一化  所以bounds=(0, 255)\n",
    "m = TensorflowModel(\n",
    "    session,\n",
    "    x,\n",
    "    None,\n",
    "    logits,\n",
    "    None,\n",
    "    bounds=(0, 255),\n",
    "    channel_axis=3,\n",
    "    preprocess=None)\n",
    "\n",
    "#实例化FGSM 进行定向攻击 \n",
    "attack = FGSMT(m)\n",
    "attack_config = {\"epsilons\": 10, \"epsilons_max\": 10, \"epsilon_steps\": 1, \"steps\": 100}\n",
    "\n",
    "adversary = Adversary(image,None)\n",
    "#麦克风\n",
    "tlabel = 651\n",
    "adversary.set_target(is_targeted_attack=True, target_label=tlabel)\n",
    "\n",
    "# FGSM targeted attack\n",
    "adversary = attack(adversary, **attack_config)\n",
    "\n",
    "if adversary.is_successful():\n",
    "    print(\n",
    "        'attack success, adversarial_label=%d'\n",
    "        % (adversary.adversarial_label) )\n",
    "\n",
    "    #对抗样本保存在adversary.adversarial_example\n",
    "    adversary_image=np.copy(adversary.adversarial_example)\n",
    "    #强制类型转换 之前是float 现在要转换成int8\n",
    "\n",
    "    adv = np.array(adversary_image).astype(\"uint8\")[0]\n",
    "\n",
    " \n",
    "\n",
    "print(\"fgsm attack done\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "l0=150379 l2=65875.2890999\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#显示原始图片  抵抗样本 以及两张图之间的差异  其中灰色代表没有差异的像素点\n",
    "show_images_diff(orig,adversary.original_label,adv,adversary.adversarial_label)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "advbox",
   "language": "python",
   "name": "advbox"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
